| Title |
Digital earth: A platform for the SDGs and green transformation at the global and local level, employing essential SDGs variables |
| ID_Doc |
62675 |
| Authors |
Fukui, H; Man, DC; Phan, A |
| Title |
Digital earth: A platform for the SDGs and green transformation at the global and local level, employing essential SDGs variables |
| Year |
2021 |
| Published |
Big Earth Data, 5, 4 |
| DOI |
10.1080/20964471.2021.1948677 |
| Abstract |
The 17 Sustainable Development Goals present clear directions toward the green transformation being sought by the global community. The SDGs are an integrated framework, with a complex network of interlinkages between the goals, targets and indicators, and they pose wicked problems to society. Consequently, measuring progress and achievements with the SDGs requires the integration of various spatio-temporal datasets from different domains and the synthesis of disciplines to describe a system of systems. The Group on Earth Observations has developed the concept of Essential Variables to describe systems across Societal Benefit Areas that are applicable for this purpose. Digital Earth is a virtual representation of the planet, potentially encompassing all its systems and life forms, including human societies. Designed as a multi-dimensional, multi-scale, multi-temporal, and multi-layer information facility, Digital Earth is a valuable platform that can contribute to the achievement of the SDGs and a green transformation. To that end, a set of Essential SDGs Variables (ESDGVs) for the platform are proposed and cases of implementation and use are introduced. |
| Author Keywords |
Digital earth; sdgs; earth observation; interoperability; essential variables |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:000691643500001 |
| WoS Category |
Computer Science, Information Systems; Geosciences, Multidisciplinary; Remote Sensing |
| Research Area |
Computer Science; Geology; Remote Sensing |
| PDF |
https://doi.org/10.1080/20964471.2021.1948677
|